How to Use the Wikidata MCP in CrewAI

Q: What is the best way to start a research project with Wikidata and crewai?

Have one agent use searchitemsvector first. This gives the whole 'crew' an initial, high-quality dataset to work with, making subsequent analysis faster.

Orchestrate multi-agent research across Wikidata autonomously with crewai.

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Connect Wikidata MCP to CrewAI

Create your Vinkius account to connect Wikidata to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Wikidata with CrewAI

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Collaborative Wikidata Research with CrewAI

Assign one agent to gather initial facts via `get_item_statements`. A second specialized agent can then take those raw statements and refine them using `get_similarity_score` to check for related concepts. The shared memory ensures all agents work off the same verified data set.

Autonomous Wikidata Monitoring with MCP Server

Set up a monitor agent that periodically runs `execute_sparql` to check for changes in specific data sets. If an unexpected result is found, it doesn't just fail—it escalates the issue by handing off control to a dedicated moderator agent for action.

Synthesize and Record Wikidata Findings using CrewAI

Use one agent to perform broad searches with `search_items_vector`. A second agent then synthesizes the findings, determines what new knowledge is required, and finally uses `create_statement` to record it autonomously.

Setup guide

Set up Wikidata MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Wikidata tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Wikidata Analyst",
    goal="Access and analyze Wikidata data via MCP.",
    backstory="Expert analyst with direct Wikidata access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Wikidata transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Wikidata Analyst",
        goal="Access and analyze Wikidata data via MCP.",
        backstory="Expert analyst with direct Wikidata access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Wikidata transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Wikidata. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Wikidata MCP in CrewAI

You assign a specialized agent solely responsible for running `execute_sparql`. This dedicated role ensures that the query logic is kept separate from the analysis and writing roles.

Absolutely. You can give one agent the task of finding two items, and another agent the job of comparing them using `get_similarity_score` against the retrieved data.

Have one agent use `search_items_vector` first. This gives the whole 'crew' an initial, high-quality dataset to work with, making subsequent analysis faster.

Use it for operations that require multiple specialized steps—like monitoring a data set and writing out the necessary corrections based on the findings.

The primary data type is structured knowledge (triples). Agents use `create_statement` to record new facts after verifying them via other tools.

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